Overview

Dataset statistics

Number of variables25
Number of observations30059
Missing cells142571
Missing cells (%)19.0%
Total size in memory6.0 MiB
Average record size in memory208.0 B

Variable types

Text17
Numeric8

Alerts

ad_type has constant value ""Constant
l1 has constant value ""Constant
l2 has constant value ""Constant
currency has constant value ""Constant
price_period has constant value ""Constant
l3 has 863 (2.9%) missing valuesMissing
l4 has 2058 (6.8%) missing valuesMissing
l5 has 2114 (7.0%) missing valuesMissing
l6 has 26405 (87.8%) missing valuesMissing
rooms has 29675 (98.7%) missing valuesMissing
bedrooms has 10351 (34.4%) missing valuesMissing
bathrooms has 724 (2.4%) missing valuesMissing
surface_total has 9847 (32.8%) missing valuesMissing
surface_covered has 29893 (99.4%) missing valuesMissing
price_period has 29668 (98.7%) missing valuesMissing
surface_total is highly skewed (γ1 = 68.84874995)Skewed
id has unique valuesUnique

Reproduction

Analysis started2025-01-07 08:39:26.065252
Analysis finished2025-01-07 08:39:29.766713
Duration3.7 seconds
Software versionydata-profiling vv4.6.0
Download configurationconfig.json

Variables

id
Text

UNIQUE 

Distinct30059
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size469.7 KiB
2025-01-07T03:39:29.995901image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters721416
Distinct characters65
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30059 ?
Unique (%)100.0%

Sample

1st rowIkdxz61f/OO1ltcy74G9xQ==
2nd rowgdgSQxXi2hfaA90JxeJqzQ==
3rd row/JYzg1QeHBe3CNMXlm7YvA==
4th rowTBX1PWRZCvwPdfVv7PSZfg==
5th rowZ2unG5O6k46dl5/xBhRcEA==
ValueCountFrequency (%)
ikdxz61f/oo1ltcy74g9xq 1
 
< 0.1%
ygcuztuygwjfwhyr4cfjbw 1
 
< 0.1%
z2ung5o6k46dl5/xbhrcea 1
 
< 0.1%
poa6espqfegmckt5vovamw 1
 
< 0.1%
bizzb0+jejvl0/ei8rdlcg 1
 
< 0.1%
w6qhhrnvvz96qfmpnbfb7g 1
 
< 0.1%
3klpjznvszqujqnanwbc6w 1
 
< 0.1%
rvz71wav4xdk8pzl8s6p1g 1
 
< 0.1%
lemzfyyznpx975goe7uarg 1
 
< 0.1%
zsoqhq5ob3uypz2+m5ypia 1
 
< 0.1%
Other values (30049) 30049
> 99.9%
2025-01-07T03:39:30.356841image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
= 60118
 
8.3%
g 17464
 
2.4%
Q 17371
 
2.4%
A 17357
 
2.4%
w 17219
 
2.4%
f 10051
 
1.4%
7 10051
 
1.4%
W 10049
 
1.4%
v 10043
 
1.4%
N 10022
 
1.4%
Other values (55) 541671
75.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 271790
37.7%
Lowercase Letter 271406
37.6%
Decimal Number 98614
 
13.7%
Math Symbol 69920
 
9.7%
Other Punctuation 9686
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
g 17464
 
6.4%
w 17219
 
6.3%
f 10051
 
3.7%
v 10043
 
3.7%
y 10016
 
3.7%
a 9995
 
3.7%
c 9979
 
3.7%
x 9934
 
3.7%
r 9919
 
3.7%
p 9907
 
3.7%
Other values (16) 156879
57.8%
Uppercase Letter
ValueCountFrequency (%)
Q 17371
 
6.4%
A 17357
 
6.4%
W 10049
 
3.7%
N 10022
 
3.7%
X 9990
 
3.7%
B 9977
 
3.7%
P 9967
 
3.7%
H 9954
 
3.7%
F 9951
 
3.7%
O 9950
 
3.7%
Other values (16) 157202
57.8%
Decimal Number
ValueCountFrequency (%)
7 10051
10.2%
1 9974
10.1%
8 9974
10.1%
2 9929
10.1%
4 9924
10.1%
5 9838
10.0%
9 9826
10.0%
6 9724
9.9%
3 9688
9.8%
0 9686
9.8%
Math Symbol
ValueCountFrequency (%)
= 60118
86.0%
+ 9802
 
14.0%
Other Punctuation
ValueCountFrequency (%)
/ 9686
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 543196
75.3%
Common 178220
 
24.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
g 17464
 
3.2%
Q 17371
 
3.2%
A 17357
 
3.2%
w 17219
 
3.2%
f 10051
 
1.9%
W 10049
 
1.8%
v 10043
 
1.8%
N 10022
 
1.8%
y 10016
 
1.8%
a 9995
 
1.8%
Other values (42) 413609
76.1%
Common
ValueCountFrequency (%)
= 60118
33.7%
7 10051
 
5.6%
1 9974
 
5.6%
8 9974
 
5.6%
2 9929
 
5.6%
4 9924
 
5.6%
5 9838
 
5.5%
9 9826
 
5.5%
+ 9802
 
5.5%
6 9724
 
5.5%
Other values (3) 29060
16.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 721416
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
= 60118
 
8.3%
g 17464
 
2.4%
Q 17371
 
2.4%
A 17357
 
2.4%
w 17219
 
2.4%
f 10051
 
1.4%
7 10051
 
1.4%
W 10049
 
1.4%
v 10043
 
1.4%
N 10022
 
1.4%
Other values (55) 541671
75.1%

ad_type
Text

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size469.7 KiB
2025-01-07T03:39:30.512169image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters270531
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPropiedad
2nd rowPropiedad
3rd rowPropiedad
4th rowPropiedad
5th rowPropiedad
ValueCountFrequency (%)
propiedad 30059
100.0%
2025-01-07T03:39:30.791477image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 60118
22.2%
P 30059
11.1%
r 30059
11.1%
o 30059
11.1%
p 30059
11.1%
i 30059
11.1%
e 30059
11.1%
a 30059
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 240472
88.9%
Uppercase Letter 30059
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 60118
25.0%
r 30059
12.5%
o 30059
12.5%
p 30059
12.5%
i 30059
12.5%
e 30059
12.5%
a 30059
12.5%
Uppercase Letter
ValueCountFrequency (%)
P 30059
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 270531
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 60118
22.2%
P 30059
11.1%
r 30059
11.1%
o 30059
11.1%
p 30059
11.1%
i 30059
11.1%
e 30059
11.1%
a 30059
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 270531
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 60118
22.2%
P 30059
11.1%
r 30059
11.1%
o 30059
11.1%
p 30059
11.1%
i 30059
11.1%
e 30059
11.1%
a 30059
11.1%
Distinct285
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size469.7 KiB
2025-01-07T03:39:31.054193image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters300590
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)0.1%

Sample

1st row2019-11-16
2nd row2019-09-13
3rd row2019-09-13
4th row2019-09-13
5th row2019-09-13
ValueCountFrequency (%)
2019-08-15 2907
 
9.7%
2019-11-08 1631
 
5.4%
2019-10-08 1127
 
3.7%
2019-10-16 685
 
2.3%
2019-08-25 675
 
2.2%
2019-08-11 652
 
2.2%
2019-06-17 641
 
2.1%
2019-09-11 503
 
1.7%
2019-09-01 396
 
1.3%
2019-06-04 364
 
1.2%
Other values (275) 20478
68.1%
2025-01-07T03:39:31.444667image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 76428
25.4%
- 60118
20.0%
2 51357
17.1%
1 48994
16.3%
9 26225
 
8.7%
8 9387
 
3.1%
5 7206
 
2.4%
3 6417
 
2.1%
4 5271
 
1.8%
6 5157
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 240472
80.0%
Dash Punctuation 60118
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 76428
31.8%
2 51357
21.4%
1 48994
20.4%
9 26225
 
10.9%
8 9387
 
3.9%
5 7206
 
3.0%
3 6417
 
2.7%
4 5271
 
2.2%
6 5157
 
2.1%
7 4030
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 60118
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 300590
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 76428
25.4%
- 60118
20.0%
2 51357
17.1%
1 48994
16.3%
9 26225
 
8.7%
8 9387
 
3.1%
5 7206
 
2.4%
3 6417
 
2.1%
4 5271
 
1.8%
6 5157
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300590
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 76428
25.4%
- 60118
20.0%
2 51357
17.1%
1 48994
16.3%
9 26225
 
8.7%
8 9387
 
3.1%
5 7206
 
2.4%
3 6417
 
2.1%
4 5271
 
1.8%
6 5157
 
1.7%
Distinct341
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size469.7 KiB
2025-01-07T03:39:31.708030image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters300590
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)0.1%

Sample

1st row2020-02-08
2nd row2019-11-27
3rd row2019-10-07
4th row2019-10-07
5th row2020-01-13
ValueCountFrequency (%)
9999-12-31 5403
18.0%
2019-08-25 3395
 
11.3%
2020-05-13 2257
 
7.5%
2019-11-27 1755
 
5.8%
2020-02-14 1389
 
4.6%
2020-01-13 1315
 
4.4%
2020-03-10 1005
 
3.3%
2019-12-16 924
 
3.1%
2019-06-08 848
 
2.8%
2019-07-25 661
 
2.2%
Other values (331) 11107
37.0%
2025-01-07T03:39:32.105421image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 60118
20.0%
0 60069
20.0%
2 50380
16.8%
1 50175
16.7%
9 40893
13.6%
3 11614
 
3.9%
5 7943
 
2.6%
8 6101
 
2.0%
7 5058
 
1.7%
6 4440
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 240472
80.0%
Dash Punctuation 60118
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 60069
25.0%
2 50380
21.0%
1 50175
20.9%
9 40893
17.0%
3 11614
 
4.8%
5 7943
 
3.3%
8 6101
 
2.5%
7 5058
 
2.1%
6 4440
 
1.8%
4 3799
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 60118
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 300590
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 60118
20.0%
0 60069
20.0%
2 50380
16.8%
1 50175
16.7%
9 40893
13.6%
3 11614
 
3.9%
5 7943
 
2.6%
8 6101
 
2.0%
7 5058
 
1.7%
6 4440
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300590
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 60118
20.0%
0 60069
20.0%
2 50380
16.8%
1 50175
16.7%
9 40893
13.6%
3 11614
 
3.9%
5 7943
 
2.6%
8 6101
 
2.0%
7 5058
 
1.7%
6 4440
 
1.5%
Distinct285
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size469.7 KiB
2025-01-07T03:39:32.364942image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters300590
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)0.1%

Sample

1st row2019-11-16
2nd row2019-09-13
3rd row2019-09-13
4th row2019-09-13
5th row2019-09-13
ValueCountFrequency (%)
2019-08-15 2907
 
9.7%
2019-11-08 1631
 
5.4%
2019-10-08 1127
 
3.7%
2019-10-16 685
 
2.3%
2019-08-25 675
 
2.2%
2019-08-11 652
 
2.2%
2019-06-17 641
 
2.1%
2019-09-11 503
 
1.7%
2019-09-01 396
 
1.3%
2019-06-04 364
 
1.2%
Other values (275) 20478
68.1%
2025-01-07T03:39:32.754701image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 76428
25.4%
- 60118
20.0%
2 51357
17.1%
1 48994
16.3%
9 26225
 
8.7%
8 9387
 
3.1%
5 7206
 
2.4%
3 6417
 
2.1%
4 5271
 
1.8%
6 5157
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 240472
80.0%
Dash Punctuation 60118
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 76428
31.8%
2 51357
21.4%
1 48994
20.4%
9 26225
 
10.9%
8 9387
 
3.9%
5 7206
 
3.0%
3 6417
 
2.7%
4 5271
 
2.2%
6 5157
 
2.1%
7 4030
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 60118
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 300590
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 76428
25.4%
- 60118
20.0%
2 51357
17.1%
1 48994
16.3%
9 26225
 
8.7%
8 9387
 
3.1%
5 7206
 
2.4%
3 6417
 
2.1%
4 5271
 
1.8%
6 5157
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300590
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 76428
25.4%
- 60118
20.0%
2 51357
17.1%
1 48994
16.3%
9 26225
 
8.7%
8 9387
 
3.1%
5 7206
 
2.4%
3 6417
 
2.1%
4 5271
 
1.8%
6 5157
 
1.7%

lat
Real number (ℝ)

Distinct5412
Distinct (%)18.2%
Missing248
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean-0.1837148547
Minimum-1.044331
Maximum0.1519999951
Zeros0
Zeros (%)0.0%
Negative29638
Negative (%)98.6%
Memory size469.7 KiB
2025-01-07T03:39:32.913036image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum-1.044331
5-th percentile-0.3070000112
Q1-0.2090000063
median-0.18224532
Q3-0.1570000052
95-th percentile-0.0890000015
Maximum0.1519999951
Range1.196330995
Interquartile range (IQR)0.0520000011

Descriptive statistics

Standard deviation0.06335680527
Coefficient of variation (CV)-0.3448649015
Kurtosis3.416327917
Mean-0.1837148547
Median Absolute Deviation (MAD)0.02524532
Skewness-0.2022968864
Sum-5476.723534
Variance0.004014084774
MonotonicityNot monotonic
2025-01-07T03:39:33.071147image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.2109999955 725
 
2.4%
-0.1819999963 537
 
1.8%
-0.1809999943 522
 
1.7%
-0.1850000024 430
 
1.4%
-0.1979999989 322
 
1.1%
-0.1659999937 320
 
1.1%
-0.1800000072 313
 
1.0%
-0.2049999982 312
 
1.0%
-0.1870000064 280
 
0.9%
-0.1570000052 276
 
0.9%
Other values (5402) 25774
85.7%
ValueCountFrequency (%)
-1.044331 1
 
< 0.1%
-0.6143454909 1
 
< 0.1%
-0.5189999938 1
 
< 0.1%
-0.5114002 6
< 0.1%
-0.51099998 2
 
< 0.1%
ValueCountFrequency (%)
0.1519999951 1
 
< 0.1%
0.150000006 1
 
< 0.1%
0.15 5
< 0.1%
0.1266098917 1
 
< 0.1%
0.1169999987 8
< 0.1%

lon
Real number (ℝ)

Distinct5207
Distinct (%)17.5%
Missing248
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean-78.49361493
Minimum-79.8268729
Maximum-78.07099915
Zeros0
Zeros (%)0.0%
Negative29811
Negative (%)99.2%
Memory size469.7 KiB
2025-01-07T03:39:33.221381image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum-79.8268729
5-th percentile-78.53294439
Q1-78.4936632
median-78.48000336
Q3-78.46399689
95-th percentile-78.4167543
Maximum-78.07099915
Range1.755873755
Interquartile range (IQR)0.0296663128

Descriptive statistics

Standard deviation0.1212692579
Coefficient of variation (CV)-0.001544956975
Kurtosis26.03935957
Mean-78.49361493
Median Absolute Deviation (MAD)0.013999939
Skewness-4.929857202
Sum-2339973.155
Variance0.01470623292
MonotonicityNot monotonic
2025-01-07T03:39:33.372291image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-78.48000336 1049
 
3.5%
-78.48400116 756
 
2.5%
-78.4940033 553
 
1.8%
-78.48100281 506
 
1.7%
-78.46800232 484
 
1.6%
-78.5 474
 
1.6%
-78.44100189 468
 
1.6%
-78.47899628 462
 
1.5%
-78.47599792 404
 
1.3%
-78.47799683 381
 
1.3%
Other values (5197) 24274
80.8%
ValueCountFrequency (%)
-79.8268729 1
 
< 0.1%
-79.46600342 3
 
< 0.1%
-79.41569519 1
 
< 0.1%
-79.39199829 1
 
< 0.1%
-79.26699829 8
< 0.1%
ValueCountFrequency (%)
-78.07099915 4
< 0.1%
-78.137 2
< 0.1%
-78.13725897 1
 
< 0.1%
-78.14183699 1
 
< 0.1%
-78.14281885 1
 
< 0.1%

l1
Text

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size469.7 KiB
2025-01-07T03:39:33.522226image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters210413
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEcuador
2nd rowEcuador
3rd rowEcuador
4th rowEcuador
5th rowEcuador
ValueCountFrequency (%)
ecuador 30059
100.0%
2025-01-07T03:39:33.797731image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 30059
14.3%
c 30059
14.3%
u 30059
14.3%
a 30059
14.3%
d 30059
14.3%
o 30059
14.3%
r 30059
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 180354
85.7%
Uppercase Letter 30059
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 30059
16.7%
u 30059
16.7%
a 30059
16.7%
d 30059
16.7%
o 30059
16.7%
r 30059
16.7%
Uppercase Letter
ValueCountFrequency (%)
E 30059
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 210413
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 30059
14.3%
c 30059
14.3%
u 30059
14.3%
a 30059
14.3%
d 30059
14.3%
o 30059
14.3%
r 30059
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 210413
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 30059
14.3%
c 30059
14.3%
u 30059
14.3%
a 30059
14.3%
d 30059
14.3%
o 30059
14.3%
r 30059
14.3%

l2
Text

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size469.7 KiB
2025-01-07T03:39:33.948531image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters270531
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPichincha
2nd rowPichincha
3rd rowPichincha
4th rowPichincha
5th rowPichincha
ValueCountFrequency (%)
pichincha 30059
100.0%
2025-01-07T03:39:34.227444image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 60118
22.2%
c 60118
22.2%
h 60118
22.2%
P 30059
11.1%
n 30059
11.1%
a 30059
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 240472
88.9%
Uppercase Letter 30059
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 60118
25.0%
c 60118
25.0%
h 60118
25.0%
n 30059
12.5%
a 30059
12.5%
Uppercase Letter
ValueCountFrequency (%)
P 30059
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 270531
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 60118
22.2%
c 60118
22.2%
h 60118
22.2%
P 30059
11.1%
n 30059
11.1%
a 30059
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 270531
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 60118
22.2%
c 60118
22.2%
h 60118
22.2%
P 30059
11.1%
n 30059
11.1%
a 30059
11.1%

l3
Text

MISSING 

Distinct7
Distinct (%)< 0.1%
Missing863
Missing (%)2.9%
Memory size469.7 KiB
2025-01-07T03:39:34.547619image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length24
Median length5
Mean length5.100219208
Min length5

Characters and Unicode

Total characters148906
Distinct characters30
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowQuito
2nd rowQuito
3rd rowQuito
4th rowQuito
5th rowQuito
ValueCountFrequency (%)
quito 28546
97.4%
rumiñahui 523
 
1.8%
cayambe 70
 
0.2%
pedro 23
 
0.1%
san 20
 
0.1%
miguel 20
 
0.1%
de 20
 
0.1%
los 20
 
0.1%
bancos 20
 
0.1%
mejia 14
 
< 0.1%
Other values (3) 36
 
0.1%
2025-01-07T03:39:34.841260image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 29639
19.9%
u 29612
19.9%
o 28655
19.2%
t 28559
19.2%
Q 28546
19.2%
a 753
 
0.5%
m 593
 
0.4%
R 523
 
0.4%
ñ 523
 
0.4%
h 523
 
0.4%
Other values (20) 980
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 119478
80.2%
Uppercase Letter 29312
 
19.7%
Space Separator 116
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 29639
24.8%
u 29612
24.8%
o 28655
24.0%
t 28559
23.9%
a 753
 
0.6%
m 593
 
0.5%
ñ 523
 
0.4%
h 523
 
0.4%
e 173
 
0.1%
y 80
 
0.1%
Other values (9) 368
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
Q 28546
97.4%
R 523
 
1.8%
C 70
 
0.2%
M 57
 
0.2%
P 23
 
0.1%
S 20
 
0.1%
D 20
 
0.1%
L 20
 
0.1%
B 20
 
0.1%
V 13
 
< 0.1%
Space Separator
ValueCountFrequency (%)
116
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 148790
99.9%
Common 116
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 29639
19.9%
u 29612
19.9%
o 28655
19.3%
t 28559
19.2%
Q 28546
19.2%
a 753
 
0.5%
m 593
 
0.4%
R 523
 
0.4%
ñ 523
 
0.4%
h 523
 
0.4%
Other values (19) 864
 
0.6%
Common
ValueCountFrequency (%)
116
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 148383
99.6%
None 523
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 29639
20.0%
u 29612
20.0%
o 28655
19.3%
t 28559
19.2%
Q 28546
19.2%
a 753
 
0.5%
m 593
 
0.4%
R 523
 
0.4%
h 523
 
0.4%
e 173
 
0.1%
Other values (19) 807
 
0.5%
None
ValueCountFrequency (%)
ñ 523
100.0%

l4
Text

MISSING 

Distinct6
Distinct (%)< 0.1%
Missing2058
Missing (%)6.8%
Memory size469.7 KiB
2025-01-07T03:39:35.003286image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length17
Median length12
Mean length12.84343416
Min length12

Characters and Unicode

Total characters359629
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCentro Norte
2nd rowCentro Norte
3rd rowCentro Norte
4th rowCentro Norte
5th rowCentro Norte
ValueCountFrequency (%)
norte 20516
32.7%
centro 17878
28.5%
de 5204
 
8.3%
quito 5204
 
8.3%
valle 4919
 
7.8%
tumbaco 3426
 
5.5%
los 1493
 
2.4%
chillos 1493
 
2.4%
colonial 1490
 
2.4%
sur 1076
 
1.7%
2025-01-07T03:39:35.302630image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 52990
14.7%
e 48517
13.5%
t 43598
12.1%
r 39470
11.0%
34698
9.6%
C 20861
 
5.8%
N 20516
 
5.7%
n 19368
 
5.4%
l 15804
 
4.4%
a 9835
 
2.7%
Other values (13) 53972
15.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 262232
72.9%
Uppercase Letter 62699
 
17.4%
Space Separator 34698
 
9.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 52990
20.2%
e 48517
18.5%
t 43598
16.6%
r 39470
15.1%
n 19368
 
7.4%
l 15804
 
6.0%
a 9835
 
3.8%
u 9706
 
3.7%
i 8187
 
3.1%
m 3426
 
1.3%
Other values (4) 11331
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
C 20861
33.3%
N 20516
32.7%
Q 5204
 
8.3%
D 5204
 
8.3%
V 4919
 
7.8%
T 3426
 
5.5%
L 1493
 
2.4%
S 1076
 
1.7%
Space Separator
ValueCountFrequency (%)
34698
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 324931
90.4%
Common 34698
 
9.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 52990
16.3%
e 48517
14.9%
t 43598
13.4%
r 39470
12.1%
C 20861
 
6.4%
N 20516
 
6.3%
n 19368
 
6.0%
l 15804
 
4.9%
a 9835
 
3.0%
u 9706
 
3.0%
Other values (12) 44266
13.6%
Common
ValueCountFrequency (%)
34698
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 359629
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 52990
14.7%
e 48517
13.5%
t 43598
12.1%
r 39470
11.0%
34698
9.6%
C 20861
 
5.8%
N 20516
 
5.7%
n 19368
 
5.4%
l 15804
 
4.4%
a 9835
 
2.7%
Other values (13) 53972
15.0%

l5
Text

MISSING 

Distinct65
Distinct (%)0.2%
Missing2114
Missing (%)7.0%
Memory size469.7 KiB
2025-01-07T03:39:35.518509image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length24
Median length8
Mean length9.307890499
Min length4

Characters and Unicode

Total characters260109
Distinct characters50
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowIñaquito
2nd rowRumipamba
3rd rowConcepción
4th rowConcepción
5th rowIñaquito
ValueCountFrequency (%)
iñaquito 8282
22.5%
cumbaya 1679
 
4.6%
rumipamba 1677
 
4.6%
san 1613
 
4.4%
jipijapa 1604
 
4.4%
conocoto 1191
 
3.2%
tumbaco 1025
 
2.8%
calderón 1012
 
2.8%
mariscal 1003
 
2.7%
sucre 1003
 
2.7%
Other values (70) 16655
45.3%
2025-01-07T03:39:35.879542image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 35253
 
13.6%
o 25112
 
9.7%
i 20421
 
7.9%
u 17489
 
6.7%
n 14391
 
5.5%
e 12092
 
4.6%
t 11905
 
4.6%
I 9786
 
3.8%
c 9211
 
3.5%
8799
 
3.4%
Other values (40) 95650
36.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 215676
82.9%
Uppercase Letter 35194
 
13.5%
Space Separator 8799
 
3.4%
Dash Punctuation 440
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 35253
16.3%
o 25112
11.6%
i 20421
 
9.5%
u 17489
 
8.1%
n 14391
 
6.7%
e 12092
 
5.6%
t 11905
 
5.5%
c 9211
 
4.3%
q 8707
 
4.0%
ñ 8373
 
3.9%
Other values (18) 52722
24.4%
Uppercase Letter
ValueCountFrequency (%)
I 9786
27.8%
C 7184
20.4%
S 2723
 
7.7%
P 2176
 
6.2%
J 2166
 
6.2%
T 1847
 
5.2%
Q 1698
 
4.8%
R 1678
 
4.8%
M 1216
 
3.5%
K 880
 
2.5%
Other values (10) 3840
 
10.9%
Space Separator
ValueCountFrequency (%)
8799
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 440
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 250870
96.4%
Common 9239
 
3.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 35253
14.1%
o 25112
 
10.0%
i 20421
 
8.1%
u 17489
 
7.0%
n 14391
 
5.7%
e 12092
 
4.8%
t 11905
 
4.7%
I 9786
 
3.9%
c 9211
 
3.7%
q 8707
 
3.5%
Other values (38) 86503
34.5%
Common
ValueCountFrequency (%)
8799
95.2%
- 440
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 249312
95.8%
None 10797
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 35253
14.1%
o 25112
 
10.1%
i 20421
 
8.2%
u 17489
 
7.0%
n 14391
 
5.8%
e 12092
 
4.9%
t 11905
 
4.8%
I 9786
 
3.9%
c 9211
 
3.7%
8799
 
3.5%
Other values (35) 84853
34.0%
None
ValueCountFrequency (%)
ñ 8373
77.5%
ó 1542
 
14.3%
í 740
 
6.9%
é 139
 
1.3%
á 3
 
< 0.1%

l6
Text

MISSING 

Distinct21
Distinct (%)0.6%
Missing26405
Missing (%)87.8%
Memory size469.7 KiB
2025-01-07T03:39:36.075321image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length21
Median length14
Mean length11.04269294
Min length6

Characters and Unicode

Total characters40350
Distinct characters33
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowLa Carolina
2nd rowMonteserrin
3rd rowGonzalez Suarez
4th rowLa Carolina
5th rowMonteserrin
ValueCountFrequency (%)
el 650
10.6%
gonzalez 647
10.6%
suarez 647
10.6%
bellavista 633
10.3%
la 579
9.5%
carolina 396
 
6.5%
monteserrin 351
 
5.7%
granda 346
 
5.7%
centeno 346
 
5.7%
batan 233
 
3.8%
Other values (20) 1289
21.1%
2025-01-07T03:39:36.401380image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 6529
16.2%
n 3766
 
9.3%
e 3664
 
9.1%
l 3388
 
8.4%
r 2715
 
6.7%
2463
 
6.1%
o 2103
 
5.2%
z 1969
 
4.9%
i 1935
 
4.8%
t 1673
 
4.1%
Other values (23) 10145
25.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 31771
78.7%
Uppercase Letter 6116
 
15.2%
Space Separator 2463
 
6.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 6529
20.6%
n 3766
11.9%
e 3664
11.5%
l 3388
10.7%
r 2715
8.5%
o 2103
 
6.6%
z 1969
 
6.2%
i 1935
 
6.1%
t 1673
 
5.3%
s 1298
 
4.1%
Other values (10) 2731
8.6%
Uppercase Letter
ValueCountFrequency (%)
C 1021
16.7%
G 993
16.2%
B 868
14.2%
S 704
11.5%
L 691
11.3%
E 650
10.6%
M 508
8.3%
I 311
 
5.1%
P 189
 
3.1%
A 165
 
2.7%
Other values (2) 16
 
0.3%
Space Separator
ValueCountFrequency (%)
2463
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 37887
93.9%
Common 2463
 
6.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 6529
17.2%
n 3766
9.9%
e 3664
9.7%
l 3388
 
8.9%
r 2715
 
7.2%
o 2103
 
5.6%
z 1969
 
5.2%
i 1935
 
5.1%
t 1673
 
4.4%
s 1298
 
3.4%
Other values (22) 8847
23.4%
Common
ValueCountFrequency (%)
2463
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40296
99.9%
None 54
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 6529
16.2%
n 3766
 
9.3%
e 3664
 
9.1%
l 3388
 
8.4%
r 2715
 
6.7%
2463
 
6.1%
o 2103
 
5.2%
z 1969
 
4.9%
i 1935
 
4.8%
t 1673
 
4.2%
Other values (22) 10091
25.0%
None
ValueCountFrequency (%)
ñ 54
100.0%

rooms
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)2.3%
Missing29675
Missing (%)98.7%
Infinite0
Infinite (%)0.0%
Mean2.5234375
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size469.7 KiB
2025-01-07T03:39:36.537133image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q33
95-th percentile5
Maximum10
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.389807228
Coefficient of variation (CV)0.5507595208
Kurtosis4.911406325
Mean2.5234375
Median Absolute Deviation (MAD)1
Skewness1.470683574
Sum969
Variance1.931564132
MonotonicityNot monotonic
2025-01-07T03:39:36.663626image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
3 149
 
0.5%
1 113
 
0.4%
2 63
 
0.2%
4 38
 
0.1%
5 11
 
< 0.1%
7 4
 
< 0.1%
10 2
 
< 0.1%
6 2
 
< 0.1%
8 2
 
< 0.1%
(Missing) 29675
98.7%
ValueCountFrequency (%)
1 113
0.4%
2 63
0.2%
3 149
0.5%
4 38
 
0.1%
5 11
 
< 0.1%
ValueCountFrequency (%)
10 2
 
< 0.1%
8 2
 
< 0.1%
7 4
 
< 0.1%
6 2
 
< 0.1%
5 11
< 0.1%

bedrooms
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)0.1%
Missing10351
Missing (%)34.4%
Infinite0
Infinite (%)0.0%
Mean2.91851025
Minimum0
Maximum16
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size469.7 KiB
2025-01-07T03:39:36.787874image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q33
95-th percentile6
Maximum16
Range16
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.593727357
Coefficient of variation (CV)0.5460756415
Kurtosis7.272978495
Mean2.91851025
Median Absolute Deviation (MAD)1
Skewness2.124706357
Sum57518
Variance2.539966888
MonotonicityNot monotonic
2025-01-07T03:39:36.920498image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
3 8762
29.1%
2 3972
 
13.2%
1 3116
 
10.4%
4 2250
 
7.5%
5 553
 
1.8%
6 334
 
1.1%
10 329
 
1.1%
7 151
 
0.5%
8 139
 
0.5%
9 94
 
0.3%
Other values (4) 8
 
< 0.1%
(Missing) 10351
34.4%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 3116
 
10.4%
2 3972
13.2%
3 8762
29.1%
4 2250
 
7.5%
ValueCountFrequency (%)
16 3
 
< 0.1%
14 2
 
< 0.1%
11 2
 
< 0.1%
10 329
1.1%
9 94
 
0.3%

bathrooms
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)< 0.1%
Missing724
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean2.665689449
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size469.7 KiB
2025-01-07T03:39:37.049513image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q33
95-th percentile5
Maximum20
Range19
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.42889486
Coefficient of variation (CV)0.5360320048
Kurtosis8.0650955
Mean2.665689449
Median Absolute Deviation (MAD)1
Skewness2.007628504
Sum78198
Variance2.041740521
MonotonicityNot monotonic
2025-01-07T03:39:37.177560image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2 10397
34.6%
3 8381
27.9%
1 4971
16.5%
4 3291
 
10.9%
5 1243
 
4.1%
6 450
 
1.5%
10 224
 
0.7%
7 169
 
0.6%
8 126
 
0.4%
9 80
 
0.3%
(Missing) 724
 
2.4%
ValueCountFrequency (%)
1 4971
16.5%
2 10397
34.6%
3 8381
27.9%
4 3291
 
10.9%
5 1243
 
4.1%
ValueCountFrequency (%)
20 3
 
< 0.1%
10 224
0.7%
9 80
 
0.3%
8 126
0.4%
7 169
0.6%

surface_total
Real number (ℝ)

MISSING  SKEWED 

Distinct873
Distinct (%)4.3%
Missing9847
Missing (%)32.8%
Infinite0
Infinite (%)0.0%
Mean227.4937661
Minimum10
Maximum81378
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size469.7 KiB
2025-01-07T03:39:37.322800image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile55
Q184
median122
Q3209
95-th percentile630
Maximum81378
Range81368
Interquartile range (IQR)125

Descriptive statistics

Standard deviation851.2090514
Coefficient of variation (CV)3.741680777
Kurtosis6028.98631
Mean227.4937661
Median Absolute Deviation (MAD)48
Skewness68.84874995
Sum4598104
Variance724556.8492
MonotonicityNot monotonic
2025-01-07T03:39:37.497327image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
120 605
 
2.0%
90 593
 
2.0%
60 578
 
1.9%
100 535
 
1.8%
80 526
 
1.7%
70 448
 
1.5%
200 416
 
1.4%
110 397
 
1.3%
150 392
 
1.3%
130 359
 
1.2%
Other values (863) 15363
51.1%
(Missing) 9847
32.8%
ValueCountFrequency (%)
10 7
< 0.1%
11 2
 
< 0.1%
12 7
< 0.1%
13 2
 
< 0.1%
18 1
 
< 0.1%
ValueCountFrequency (%)
81378 1
 
< 0.1%
67450 1
 
< 0.1%
14000 3
< 0.1%
11100 2
< 0.1%
10400 1
 
< 0.1%

surface_covered
Real number (ℝ)

MISSING 

Distinct87
Distinct (%)52.4%
Missing29893
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean127.5361446
Minimum10
Maximum1316
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size469.7 KiB
2025-01-07T03:39:37.650189image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile45.25
Q165.25
median93
Q3143
95-th percentile343.75
Maximum1316
Range1306
Interquartile range (IQR)77.75

Descriptive statistics

Standard deviation132.3718198
Coefficient of variation (CV)1.037916116
Kurtosis40.87867975
Mean127.5361446
Median Absolute Deviation (MAD)29
Skewness5.365903363
Sum21171
Variance17522.29869
MonotonicityNot monotonic
2025-01-07T03:39:37.801222image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
64 11
 
< 0.1%
110 7
 
< 0.1%
90 7
 
< 0.1%
87 5
 
< 0.1%
70 5
 
< 0.1%
93 4
 
< 0.1%
66 4
 
< 0.1%
72 4
 
< 0.1%
100 4
 
< 0.1%
120 3
 
< 0.1%
Other values (77) 112
 
0.4%
(Missing) 29893
99.4%
ValueCountFrequency (%)
10 2
< 0.1%
12 1
< 0.1%
15 1
< 0.1%
18 2
< 0.1%
35 1
< 0.1%
ValueCountFrequency (%)
1316 1
< 0.1%
650 1
< 0.1%
500 1
< 0.1%
475 1
< 0.1%
474 1
< 0.1%

price
Real number (ℝ)

Distinct2670
Distinct (%)9.0%
Missing228
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean121967.4496
Minimum0
Maximum14000000
Zeros21
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size469.7 KiB
2025-01-07T03:39:37.949520image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile360
Q1700
median85000
Q3159000
95-th percentile380000
Maximum14000000
Range14000000
Interquartile range (IQR)158300

Descriptive statistics

Standard deviation234861.8679
Coefficient of variation (CV)1.925611043
Kurtosis687.9884872
Mean121967.4496
Median Absolute Deviation (MAD)84200
Skewness17.69347557
Sum3638410990
Variance5.516009701 × 1010
MonotonicityNot monotonic
2025-01-07T03:39:38.099732image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
500 738
 
2.5%
550 669
 
2.2%
600 626
 
2.1%
450 544
 
1.8%
650 485
 
1.6%
700 406
 
1.4%
400 375
 
1.2%
85000 351
 
1.2%
110000 319
 
1.1%
120000 315
 
1.0%
Other values (2660) 25003
83.2%
ValueCountFrequency (%)
0 21
0.1%
12 1
 
< 0.1%
30 1
 
< 0.1%
50 6
 
< 0.1%
55 1
 
< 0.1%
ValueCountFrequency (%)
14000000 1
< 0.1%
9700300 1
< 0.1%
9000000 1
< 0.1%
7000000 2
< 0.1%
6000000 1
< 0.1%

currency
Text

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing249
Missing (%)0.8%
Memory size469.7 KiB
2025-01-07T03:39:38.229264image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters89430
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUSD
2nd rowUSD
3rd rowUSD
4th rowUSD
5th rowUSD
ValueCountFrequency (%)
usd 29810
100.0%
2025-01-07T03:39:38.485784image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 29810
33.3%
S 29810
33.3%
D 29810
33.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 89430
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 29810
33.3%
S 29810
33.3%
D 29810
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 89430
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 29810
33.3%
S 29810
33.3%
D 29810
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 89430
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 29810
33.3%
S 29810
33.3%
D 29810
33.3%

price_period
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing29668
Missing (%)98.7%
Memory size469.7 KiB
2025-01-07T03:39:38.632556image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters2737
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMensual
2nd rowMensual
3rd rowMensual
4th rowMensual
5th rowMensual
ValueCountFrequency (%)
mensual 391
100.0%
2025-01-07T03:39:39.098377image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 391
14.3%
e 391
14.3%
n 391
14.3%
s 391
14.3%
u 391
14.3%
a 391
14.3%
l 391
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2346
85.7%
Uppercase Letter 391
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 391
16.7%
n 391
16.7%
s 391
16.7%
u 391
16.7%
a 391
16.7%
l 391
16.7%
Uppercase Letter
ValueCountFrequency (%)
M 391
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2737
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 391
14.3%
e 391
14.3%
n 391
14.3%
s 391
14.3%
u 391
14.3%
a 391
14.3%
l 391
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2737
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 391
14.3%
e 391
14.3%
n 391
14.3%
s 391
14.3%
u 391
14.3%
a 391
14.3%
l 391
14.3%

title
Text

Distinct24629
Distinct (%)81.9%
Missing0
Missing (%)0.0%
Memory size469.7 KiB
2025-01-07T03:39:39.413604image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length120
Median length93
Mean length57.32625836
Min length5

Characters and Unicode

Total characters1723170
Distinct characters125
Distinct categories17 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21034 ?
Unique (%)70.0%

Sample

1st rowDepartamentos alquiler
2nd rowVenta de Casa en Capelo. 3 Plantas en Conjunto Privado
3rd rowRENTO AMPLIA CASA EN UNA PLANTA, SECTOR BRASIL
4th rowRenta o Arriendo Departamento, Sector Republica de Salvador, Centro Norte
5th rowH/ Sector Andalucía! Departamento en venta 118m² 75.000 USD
ValueCountFrequency (%)
de 16994
 
6.3%
en 14029
 
5.2%
venta 12753
 
4.7%
departamento 12280
 
4.5%
casa 9894
 
3.6%
sector 8342
 
3.1%
6132
 
2.3%
la 6052
 
2.2%
quito 4960
 
1.8%
arriendo 4283
 
1.6%
Other values (9013) 175490
64.7%
2025-01-07T03:39:39.893637image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
243875
 
14.2%
a 140476
 
8.2%
e 127643
 
7.4%
o 93915
 
5.5%
n 82373
 
4.8%
t 76954
 
4.5%
r 73210
 
4.2%
i 57379
 
3.3%
A 49106
 
2.8%
d 46500
 
2.7%
Other values (115) 731739
42.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 961948
55.8%
Uppercase Letter 410477
23.8%
Space Separator 243903
 
14.2%
Decimal Number 55718
 
3.2%
Other Punctuation 43852
 
2.5%
Dash Punctuation 4169
 
0.2%
Currency Symbol 757
 
< 0.1%
Other Number 643
 
< 0.1%
Connector Punctuation 486
 
< 0.1%
Close Punctuation 456
 
< 0.1%
Other values (7) 761
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 140476
14.6%
e 127643
13.3%
o 93915
9.8%
n 82373
8.6%
t 76954
8.0%
r 73210
7.6%
i 57379
 
6.0%
d 46500
 
4.8%
s 42006
 
4.4%
l 41818
 
4.3%
Other values (29) 179674
18.7%
Uppercase Letter
ValueCountFrequency (%)
A 49106
12.0%
E 42654
10.4%
C 32964
 
8.0%
O 30537
 
7.4%
S 29527
 
7.2%
D 27225
 
6.6%
R 27159
 
6.6%
N 26381
 
6.4%
T 24657
 
6.0%
L 18921
 
4.6%
Other values (26) 101346
24.7%
Other Punctuation
ValueCountFrequency (%)
, 27629
63.0%
. 7552
 
17.2%
/ 5878
 
13.4%
! 1815
 
4.1%
: 520
 
1.2%
" 140
 
0.3%
· 96
 
0.2%
* 46
 
0.1%
; 45
 
0.1%
% 30
 
0.1%
Other values (9) 101
 
0.2%
Decimal Number
ValueCountFrequency (%)
2 12272
22.0%
0 10443
18.7%
1 8213
14.7%
3 6873
12.3%
5 4456
 
8.0%
4 3585
 
6.4%
6 2773
 
5.0%
8 2503
 
4.5%
9 2469
 
4.4%
7 2131
 
3.8%
Math Symbol
ValueCountFrequency (%)
| 169
84.1%
+ 26
 
12.9%
> 3
 
1.5%
< 3
 
1.5%
Space Separator
ValueCountFrequency (%)
243875
> 99.9%
  28
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 3868
92.8%
301
 
7.2%
Other Number
ValueCountFrequency (%)
² 642
99.8%
½ 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 455
99.8%
} 1
 
0.2%
Final Punctuation
ValueCountFrequency (%)
50
98.0%
1
 
2.0%
Currency Symbol
ValueCountFrequency (%)
$ 757
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 486
100.0%
Open Punctuation
ValueCountFrequency (%)
( 454
100.0%
Initial Punctuation
ValueCountFrequency (%)
51
100.0%
Other Symbol
ValueCountFrequency (%)
° 2
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Format
ValueCountFrequency (%)
 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1372425
79.6%
Common 350745
 
20.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 140476
 
10.2%
e 127643
 
9.3%
o 93915
 
6.8%
n 82373
 
6.0%
t 76954
 
5.6%
r 73210
 
5.3%
i 57379
 
4.2%
A 49106
 
3.6%
d 46500
 
3.4%
E 42654
 
3.1%
Other values (65) 582215
42.4%
Common
ValueCountFrequency (%)
243875
69.5%
, 27629
 
7.9%
2 12272
 
3.5%
0 10443
 
3.0%
1 8213
 
2.3%
. 7552
 
2.2%
3 6873
 
2.0%
/ 5878
 
1.7%
5 4456
 
1.3%
- 3868
 
1.1%
Other values (40) 19686
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1712197
99.4%
None 10563
 
0.6%
Punctuation 410
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
243875
 
14.2%
a 140476
 
8.2%
e 127643
 
7.5%
o 93915
 
5.5%
n 82373
 
4.8%
t 76954
 
4.5%
r 73210
 
4.3%
i 57379
 
3.4%
A 49106
 
2.9%
d 46500
 
2.7%
Other values (79) 720766
42.1%
None
ValueCountFrequency (%)
ó 2477
23.4%
ñ 2010
19.0%
á 1426
13.5%
í 1087
10.3%
ú 996
9.4%
² 642
 
6.1%
é 482
 
4.6%
Ó 314
 
3.0%
Á 245
 
2.3%
Ñ 213
 
2.0%
Other values (21) 671
 
6.4%
Punctuation
ValueCountFrequency (%)
301
73.4%
51
 
12.4%
50
 
12.2%
7
 
1.7%
1
 
0.2%
Distinct25911
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Memory size469.7 KiB
2025-01-07T03:39:40.232959image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length6047
Median length1713
Mean length575.3769254
Min length6

Characters and Unicode

Total characters17295255
Distinct characters185
Distinct categories21 ?
Distinct scripts4 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23151 ?
Unique (%)77.0%

Sample

1st rowSuite de renta amoblada Av. República del Salvador. 69 metros, con pisos de madera flotante, cocina abierta. dormitorio amplio con tv grande. baño con tina. Garaje. Edif con guardianía 24 horas. Sector comercial residencial, cerca a centros comerciales, bancos, restaurantes, parque de La Carolina. Precio 550 con condominio citas solo al celular 0999804857
2nd rowVenta de Casa en Capelo. 3 Plantas en Conjunto Privado<br>Urbana De Negocios Vende Casa de 3 plantas. <br>120 Mts. <br>Ubicado en Capelo. <br>Sala. <br>Comedor. <br>Cocina. <br>3 Dormitorios. <br>Patio. <br>Balcon. <br>2 Baños Completos. <br>1 Medio baño. <br>La casa se encuentra ubicada dentro de un conjunto privado cuenta con guardiania 24 horas áreas de juego cancha. <br>CMM <br>Para mayor información comunícate con nosotros que con gusto te atenderemos. <br>Marines Montaluisa 0992575843 <br>Nilvis Rendon 0962690690 <br>Urbana De Negocios. <br>Mas que un negocio una Inversión.
3rd rowRENTO AMPLIA CASA EN UNA PLANTA, SECTOR BRASIL<br><br>Cerca de transporte publico, universidad Cordillera.<br><br>Remodelada, sala comedor cocina, 3 dormitorios, estudio, área de servicio completo, 1 1/2 baños, cortinas, patio, 4 parqueaderos, se acepta mascota pequeña educada. CONTACTO: 0984075230
4th rowRento Departamento Sin Muebles, Sector Republica de Salvador<br><br>Piso alto de edificio con ascensor<br>Sala comedor, cocina cerrada con desayunador, <br>3 dormitorios, 2 baños, piso flotante, cortinas, área de maquinas en torre, gas centralizado, 2 parqueaderos, 1 bodega, áreas comunales: gym, terraza, bbqq, sauna, turco, guardia 24h. CONTACTO: 0984075230. Valor incluye alícuota.
5th rowHermoso departamento en venta, ubicado por el sector Andalucía <br><br>7 piso con ascensor<br><br>Departamento N 703<br>Área de 118 m²<br>3 Dormitorios. <br>2 Baños completos. <br>Sala Comedor<br>Cocina tradicional <br>Hermosa vista a la ciudad.<br>1 Parquedero sub suelo <br>Precio de venta 75.000 USD negociables <br>Alícuota de 34 USD incluye el consumo de agua.<br>25 años de construido.<br><br>Para mayor información y citas<br><br>Contacte a<br><br>Ing. Henry Marea<br>0983564292<br>Ing. Hilda Torres<br>0989372794<br>Asesores Inmobiliarios Independientes
ValueCountFrequency (%)
de 169132
 
7.1%
con 72639
 
3.1%
y 72029
 
3.0%
48669
 
2.0%
en 47071
 
2.0%
la 31223
 
1.3%
a 27387
 
1.2%
baño 27094
 
1.1%
el 23670
 
1.0%
2 21181
 
0.9%
Other values (87192) 1840611
77.3%
2025-01-07T03:39:40.732475image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2291757
 
13.3%
a 1321952
 
7.6%
e 1131107
 
6.5%
r 1001450
 
5.8%
o 991041
 
5.7%
i 714549
 
4.1%
n 690545
 
4.0%
s 649513
 
3.8%
c 588715
 
3.4%
t 523913
 
3.0%
Other values (175) 7390713
42.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10586118
61.2%
Uppercase Letter 2508733
 
14.5%
Space Separator 2298616
 
13.3%
Decimal Number 607666
 
3.5%
Math Symbol 584855
 
3.4%
Other Punctuation 449223
 
2.6%
Control 156448
 
0.9%
Dash Punctuation 73713
 
0.4%
Open Punctuation 10090
 
0.1%
Close Punctuation 10087
 
0.1%
Other values (11) 9706
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1321952
12.5%
e 1131107
10.7%
r 1001450
9.5%
o 991041
9.4%
i 714549
 
6.7%
n 690545
 
6.5%
s 649513
 
6.1%
c 588715
 
5.6%
t 523913
 
4.9%
d 521884
 
4.9%
Other values (50) 2451449
23.2%
Uppercase Letter
ValueCountFrequency (%)
A 309525
12.3%
E 248050
 
9.9%
C 205849
 
8.2%
O 193160
 
7.7%
S 177939
 
7.1%
I 161998
 
6.5%
N 154069
 
6.1%
R 150849
 
6.0%
D 127549
 
5.1%
T 120076
 
4.8%
Other values (35) 659669
26.3%
Other Punctuation
ValueCountFrequency (%)
, 186158
41.4%
. 113371
25.2%
: 62138
 
13.8%
29867
 
6.6%
* 17782
 
4.0%
/ 15888
 
3.5%
# 6729
 
1.5%
! 5803
 
1.3%
; 3143
 
0.7%
% 2123
 
0.5%
Other values (11) 6221
 
1.4%
Decimal Number
ValueCountFrequency (%)
0 115612
19.0%
2 108291
17.8%
1 81068
13.3%
9 67688
11.1%
3 52740
8.7%
5 44878
 
7.4%
4 39870
 
6.6%
8 37891
 
6.2%
7 29922
 
4.9%
6 29706
 
4.9%
Math Symbol
ValueCountFrequency (%)
> 291888
49.9%
< 291875
49.9%
+ 767
 
0.1%
= 252
 
< 0.1%
| 47
 
< 0.1%
23
 
< 0.1%
× 2
 
< 0.1%
¬ 1
 
< 0.1%
Other Symbol
ValueCountFrequency (%)
255
58.1%
° 139
31.7%
35
 
8.0%
7
 
1.6%
2
 
0.5%
1
 
0.2%
Control
ValueCountFrequency (%)
149069
95.3%
3788
 
2.4%
3591
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 72332
98.1%
1358
 
1.8%
23
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 10070
99.8%
] 13
 
0.1%
} 4
 
< 0.1%
Other Number
ValueCountFrequency (%)
² 1016
83.1%
½ 205
 
16.8%
¾ 1
 
0.1%
Final Punctuation
ValueCountFrequency (%)
282
82.7%
40
 
11.7%
» 19
 
5.6%
Modifier Symbol
ValueCountFrequency (%)
´ 30
54.5%
¨ 22
40.0%
^ 3
 
5.5%
Format
ValueCountFrequency (%)
22
81.5%
3
 
11.1%
2
 
7.4%
Space Separator
ValueCountFrequency (%)
2291757
99.7%
  6859
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 10076
99.9%
[ 14
 
0.1%
Other Letter
ValueCountFrequency (%)
º 555
98.9%
ª 6
 
1.1%
Initial Punctuation
ValueCountFrequency (%)
310
90.4%
33
 
9.6%
Nonspacing Mark
ValueCountFrequency (%)
279
99.3%
́ 2
 
0.7%
Private Use
ValueCountFrequency (%)
96
99.0%
1
 
1.0%
Currency Symbol
ValueCountFrequency (%)
$ 5579
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 761
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13095412
75.7%
Common 4199463
 
24.3%
Inherited 283
 
< 0.1%
Unknown 97
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1321952
 
10.1%
e 1131107
 
8.6%
r 1001450
 
7.6%
o 991041
 
7.6%
i 714549
 
5.5%
n 690545
 
5.3%
s 649513
 
5.0%
c 588715
 
4.5%
t 523913
 
4.0%
d 521884
 
4.0%
Other values (97) 4960743
37.9%
Common
ValueCountFrequency (%)
2291757
54.6%
> 291888
 
7.0%
< 291875
 
7.0%
, 186158
 
4.4%
149069
 
3.5%
0 115612
 
2.8%
. 113371
 
2.7%
2 108291
 
2.6%
1 81068
 
1.9%
- 72332
 
1.7%
Other values (63) 498042
 
11.9%
Inherited
ValueCountFrequency (%)
279
98.6%
́ 2
 
0.7%
2
 
0.7%
Unknown
ValueCountFrequency (%)
96
99.0%
1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17005187
98.3%
None 257169
 
1.5%
Punctuation 32198
 
0.2%
VS 279
 
< 0.1%
Misc Symbols 258
 
< 0.1%
PUA 97
 
< 0.1%
Dingbats 35
 
< 0.1%
Arrows 23
 
< 0.1%
Geometric Shapes 7
 
< 0.1%
Diacriticals 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2291757
 
13.5%
a 1321952
 
7.8%
e 1131107
 
6.7%
r 1001450
 
5.9%
o 991041
 
5.8%
i 714549
 
4.2%
n 690545
 
4.1%
s 649513
 
3.8%
c 588715
 
3.5%
t 523913
 
3.1%
Other values (85) 7100645
41.8%
None
ValueCountFrequency (%)
ó 52657
20.5%
ñ 49132
19.1%
á 42104
16.4%
í 36866
14.3%
Á 19182
 
7.5%
é 11965
 
4.7%
Ó 10685
 
4.2%
ú 7342
 
2.9%
  6859
 
2.7%
Ñ 6346
 
2.5%
Other values (58) 14031
 
5.5%
Punctuation
ValueCountFrequency (%)
29867
92.8%
1358
 
4.2%
310
 
1.0%
282
 
0.9%
256
 
0.8%
40
 
0.1%
33
 
0.1%
23
 
0.1%
22
 
0.1%
3
 
< 0.1%
Other values (2) 4
 
< 0.1%
VS
ValueCountFrequency (%)
279
100.0%
Misc Symbols
ValueCountFrequency (%)
255
98.8%
2
 
0.8%
1
 
0.4%
PUA
ValueCountFrequency (%)
96
99.0%
1
 
1.0%
Dingbats
ValueCountFrequency (%)
35
100.0%
Arrows
ValueCountFrequency (%)
23
100.0%
Geometric Shapes
ValueCountFrequency (%)
7
100.0%
Diacriticals
ValueCountFrequency (%)
́ 2
100.0%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size469.7 KiB
2025-01-07T03:39:40.900397image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length12
Median length12
Mean length9.009015603
Min length2

Characters and Unicode

Total characters270802
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDepartamento
2nd rowCasa
3rd rowCasa
4th rowDepartamento
5th rowDepartamento
ValueCountFrequency (%)
departamento 18825
62.6%
casa 11217
37.3%
ph 17
 
0.1%
2025-01-07T03:39:41.199816image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 60084
22.2%
e 37650
13.9%
t 37650
13.9%
D 18825
 
7.0%
p 18825
 
7.0%
r 18825
 
7.0%
m 18825
 
7.0%
n 18825
 
7.0%
o 18825
 
7.0%
C 11217
 
4.1%
Other values (3) 11251
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 240726
88.9%
Uppercase Letter 30076
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 60084
25.0%
e 37650
15.6%
t 37650
15.6%
p 18825
 
7.8%
r 18825
 
7.8%
m 18825
 
7.8%
n 18825
 
7.8%
o 18825
 
7.8%
s 11217
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
D 18825
62.6%
C 11217
37.3%
P 17
 
0.1%
H 17
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 270802
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 60084
22.2%
e 37650
13.9%
t 37650
13.9%
D 18825
 
7.0%
p 18825
 
7.0%
r 18825
 
7.0%
m 18825
 
7.0%
n 18825
 
7.0%
o 18825
 
7.0%
C 11217
 
4.1%
Other values (3) 11251
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 270802
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 60084
22.2%
e 37650
13.9%
t 37650
13.9%
D 18825
 
7.0%
p 18825
 
7.0%
r 18825
 
7.0%
m 18825
 
7.0%
n 18825
 
7.0%
o 18825
 
7.0%
C 11217
 
4.1%
Other values (3) 11251
 
4.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size469.7 KiB
2025-01-07T03:39:41.349739image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length8
Median length5
Mean length6.09614425
Min length5

Characters and Unicode

Total characters183244
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAlquiler
2nd rowVenta
3rd rowAlquiler
4th rowAlquiler
5th rowVenta
ValueCountFrequency (%)
venta 19076
63.5%
alquiler 10983
36.5%
2025-01-07T03:39:41.628839image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 30059
16.4%
l 21966
12.0%
V 19076
10.4%
n 19076
10.4%
t 19076
10.4%
a 19076
10.4%
A 10983
 
6.0%
q 10983
 
6.0%
u 10983
 
6.0%
i 10983
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 153185
83.6%
Uppercase Letter 30059
 
16.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 30059
19.6%
l 21966
14.3%
n 19076
12.5%
t 19076
12.5%
a 19076
12.5%
q 10983
 
7.2%
u 10983
 
7.2%
i 10983
 
7.2%
r 10983
 
7.2%
Uppercase Letter
ValueCountFrequency (%)
V 19076
63.5%
A 10983
36.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 183244
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 30059
16.4%
l 21966
12.0%
V 19076
10.4%
n 19076
10.4%
t 19076
10.4%
a 19076
10.4%
A 10983
 
6.0%
q 10983
 
6.0%
u 10983
 
6.0%
i 10983
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 183244
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 30059
16.4%
l 21966
12.0%
V 19076
10.4%
n 19076
10.4%
t 19076
10.4%
a 19076
10.4%
A 10983
 
6.0%
q 10983
 
6.0%
u 10983
 
6.0%
i 10983
 
6.0%